The empirical mode decomposition (EMD) developed by Huang etc. of NASA is an advanced method for signal analysis. But there is an involved end issue in the course of getting two envelops of the data using spline inter...
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The empirical mode decomposition (EMD) developed by Huang etc. of NASA is an advanced method for signal analysis. But there is an involved end issue in the course of getting two envelops of the data using spline interpolation. A self-adaptive method to dealing with the end issue is proposed. Generally, it extends the externa sequence near the ends of the data by the most suited sequence in the inner data. For the chosen inner sequence has the most similarity of tendency with the ends, the data extension is reasonable. After the extension, the spline does not swing at both ends of the data. The result of experiment proved that the method can be used to solve the end issue effectively.
Classification is an essential technology in Pedestrian Detection System (PDS). Until now, single-classifier and basic cascaded classifier had been widely used in PDS;however, most of them can hardly satisfy the 3 req...
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Classification is an essential technology in Pedestrian Detection System (PDS). Until now, single-classifier and basic cascaded classifier had been widely used in PDS;however, most of them can hardly satisfy the 3 requirements at the same time: high detection speed, high detection rate and low false positive rate. In this paper, we proposed an optimized hierarchical classifier which can satisfy the 3 requirements. The proposed method adopted Corse-to-fine and Early-rejection principles to achieve global high performance. It consists of two hierarchies, the first one is used to quickly reject non-pedestrian objects and select out only a few candidates;the second one makes further verification to these candidates. Furthermore, each hierarchy was optimized with statistical models basing on experiments;and each hierarchy is a treelike classifier which has specific optimization demands. At last, an overall performance evaluation standard is proposed, and the experimental results showed that the proposed classifier had better overall performance.
A hierarchical MAS (multi-agent system) based on a multi-level discrete space and microscopic agent model for signal transduction network modeling and simulation was proposed. The space can effectively represent the h...
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A hierarchical MAS (multi-agent system) based on a multi-level discrete space and microscopic agent model for signal transduction network modeling and simulation was proposed. The space can effectively represent the heterogeneous cellular space, and is adaptable for systemic expansion. Moreover, the different deformations of one molecular species are packed in one mesoscopic molecule-agent, so that the global complexity is handled by the local state-space, reducing the external communications and computational complexity. The results from simulating two feedback models of MAPK (Mitogen-Activated Protein Kinase) pathway are similar to those of chemical kinetic model, showing the validity of this method.
Non-orthogonal multiple access (NOMA) assisted semi-grant-free (SGF) transmission has recently received significant research attention due to its outstanding ability of serving grant-free (GF) users with grant-based (...
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With the rapid proliferation of smart devices in wireless networks, more powerful technologies are expected to fulfill the network requirements of high throughput, massive connectivity, and diversify quality of servic...
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An active reconfigurable intelligent surface (RIS)-aided multi-user downlink communication system is investigated, where non-orthogonal multiple access (NOMA) is employed to improve spectral efficiency, and the active...
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The combination of energy harvesting (EH), cognitive radio (CR), and non-orthogonal multiple access (NOMA) is a promising solution to improve energy efficiency and spectral efficiency of the upcoming beyond fifth gene...
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